Triple
T12082652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | سيف الإسلام معمر القذافي |
E287717
|
entity |
| Predicate | مجال_التأثير |
P2828
|
FINISHED |
| Object | السياسة الليبية الداخلية |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: السياسة الليبية الداخلية | Statement: [سيف الإسلام معمر القذافي, مجال_التأثير, السياسة الليبية الداخلية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: مجال_التأثير Context triple: [سيف الإسلام معمر القذافي, مجال_التأثير, السياسة الليبية الداخلية]
-
A.
typeOfInfluence
Indicates the specific nature or category of influence that one entity exerts on another.
-
B.
impactRegion
Indicates the geographic or spatial area that is affected or influenced by a particular event, action, or phenomenon.
-
C.
influencedPolicyArea
Indicates that one entity has affected, shaped, or guided the development, direction, or implementation of a particular policy area associated with another entity.
-
D.
placeOfInfluence
Indicates the location or area where an entity exerts significant impact, authority, or cultural, social, or intellectual influence.
-
E.
sphereOfInfluence
chosen
Indicates the area or domain within which an entity exerts significant control, impact, or authority over others.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9178ad99c8190a54777b9bbe998bc |
completed | April 10, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69d915000454819089fee00022055599 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:48 p.m.